[1]} have categorized the stereo methods according to their cost optimization strategies into local and global methods. While the first group of algorithms only optimize the cost volume in a locally confined window and make implicit smoothness assumptions, global methods explicitly state their regularization scheme and perform an optimization within the whole image domain. Global methods will thus produce more accurate disparity maps compared to those estimated by local methods. Yet, at the same time, the use of global methods for embedded stereo processing is not feasible due to their complexity.
